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In this paper, we propose a dynamically low-dimensional approximation method to solve a class of time-dependent multiscale stochastic diffusion equations. A dynamically bi-orthogonal (DyBO) method was developed to explore low-dimensional…

Numerical Analysis · Mathematics 2019-02-05 Eric T. Chung , Sai-Mang Pun , Zhiwen Zhang

We consider a time-dependent linear diffusion equation together with a related inverse boundary value problem. The aim of the inverse problem is to determine, based on observations on the boundary, the non-homogeneous diffusion coefficient…

Numerical Analysis · Mathematics 2016-09-21 Lauri Mustonen

This paper is devoted to the numerical analysis of a piecewise constant discontinuous Galerkin method for time fractional subdiffusion problems. The regularity of weak solution is firstly established by using variational approach and…

Numerical Analysis · Mathematics 2022-02-22 Binjie Li , Hao Luo , Xiaoping Xie

Time-stepping $hp$-versions discontinuous Galerkin (DG) methods for the numerical solution of fractional subdiffusion problems of order $-\alpha$ with $-1<\alpha<0$ will be proposed and analyzed. Generic $hp$-version error estimates are…

Numerical Analysis · Mathematics 2014-09-25 Kassem Mustapha

In this work, we present a novel error analysis for recovering a spatially dependent diffusion coefficient in an elliptic or parabolic problem. It is based on the standard regularized output least-squares formulation with an $H^1(\Omega)$…

Numerical Analysis · Mathematics 2020-10-07 Bangti Jin , Zhi Zhou

Deep learning-based numerical schemes such as Physically Informed Neural Networks (PINNs) have recently emerged as an alternative to classical numerical schemes for solving Partial Differential Equations (PDEs). They are very appealing at…

Numerical Analysis · Mathematics 2022-05-11 A. Beguinet , V. Ehrlacher , R. Flenghi , M. Fuente , O. Mula , A. Somacal

We introduce a new iterative method for computing solutions of elliptic equations with random rapidly oscillating coefficients. Similarly to a multigrid method, each step of the iteration involves different computations meant to address…

Numerical Analysis · Mathematics 2020-03-31 S. Armstrong , A. Hannukainen , T. Kuusi , J. -C. Mourrat

Many scientific and engineering challenges can be formulated as optimization problems which are constrained by partial differential equations (PDEs). These include inverse problems, control problems, and design problems. As a major…

Optimization and Control · Mathematics 2017-12-25 Lasse Hjuler Christiansen , John Bagterp Jørgensen

In this article we propose a scheme for solving the coupled time-fractional nonlocal diffusion problem. The scheme consist of fractional Crank-Nicolson method with Galerkin finite element method (FEM) and Newton's method. We derive \emph{a…

Numerical Analysis · Mathematics 2023-06-06 Pari J. Kundaliya

We introduce a new variational method for the numerical homogenization of divergence form elliptic, parabolic and hyperbolic equations with arbitrary rough ($L^\infty$) coefficients. Our method does not rely on concepts of ergodicity or…

Numerical Analysis · Mathematics 2019-02-20 Houman Owhadi , Lei Zhang , Leonid Berlyand

In this paper a finite difference/local discontinuous Galerkin method for the fractional diffusion-wave equation is presented and analyzed. We first propose a new finite difference method to approximate the time fractional derivatives, and…

Numerical Analysis · Mathematics 2015-07-29 Leilei Wei

This paper aims at an accurate and efficient computation of effective quantities, e.g., the homogenized coefficients for approximating the solutions to partial differential equations with oscillatory coefficients. Typical multiscale methods…

Numerical Analysis · Mathematics 2021-03-08 Assyr Abdulle , Doghonay Arjmand , Edoardo Paganoni

This paper presents a hybrid numerical method for linear collisional kinetic equations with diffusive scaling. The aim of the method is to reduce the computational cost of kinetic equations by taking advantage of the lower dimensionality of…

Numerical Analysis · Mathematics 2022-02-09 Tino Laidin

This paper, as the sequel to previous work, develops numerical schemes for fractional diffusion equations on a two-dimensional finite domain with triangular meshes. We adopt the nodal discontinuous Galerkin methods for the full spatial…

Numerical Analysis · Mathematics 2015-07-14 Liangliang Qiu , Weihua Deng , Jan Hesthaven

It is known that standard stochastic Galerkin methods face challenges when solving partial differential equations (PDEs) with random inputs. These challenges are typically attributed to the large number of required physical basis functions…

Numerical Analysis · Mathematics 2025-08-27 Guanjie Wang , Qifeng Liao

We develop a Petrov-Galerkin stabilization method for multiscale convection-diffusion transport systems. Existing stabilization techniques add a limited number of degrees of freedom in the form of bubble functions or a modified diffusion,…

Numerical Analysis · Mathematics 2016-04-20 Victor M. Calo , Eric T. Chung , Yalchin Efendiev , Wing Tat Leung

A hybridized discontinuous Galerkin method is proposed for solving 2D fractional convection-diffusion equations containing derivatives of fractional order in space on a finite domain. The Riemann-Liouville derivative is used for the spatial…

Numerical Analysis · Mathematics 2016-07-12 Shuqin Wang , Jinyun Yuan , Weihua Deng , Yujiang Wu

Local discontinuous Galerkin methods are developed for solving second order and fourth order time-dependent partial differential equations defined on static 2D manifolds. These schemes are second-order accurate with surfaces triangulized by…

Numerical Analysis · Mathematics 2024-01-05 Shixin Xu , Zhiliang Xu

An unsteady problem is considered for a space-fractional diffusion equation in a bounded domain. A first-order evolutionary equation containing a fractional power of an elliptic operator of second order is studied for general boundary…

Numerical Analysis · Computer Science 2014-12-19 Petr N. Vabishchevich

We consider model order reduction by proper orthogonal decomposition (POD) for parametrized partial differential equations, where the underlying snapshots are computed with adaptive finite elements. We address computational and theoretical…

Numerical Analysis · Mathematics 2016-09-21 Sebastian Ullmann , Marko Rotkvic , Jens Lang